Abstract

The continuous evolution of mobile communication networks and the growing demand for reliable connectivity have made network performance optimization a central concern for mobile operators, particularly in developing regions such as Cameroon. Conventional drive test (DT) tools such as TEMS Investigation remain costly, vendor-dependent and largely inaccessible to academic institutions and small-scale operators. This work presents the design and implementation of a lightweight, standalone Android Drive Test Tool capable of real-time acquisition, visualization and reporting of cellular Key Performance Indicators (KPIs). The system was developed following the Rapid Application Development (RAD) methodology and adopts a single-tier mobile architecture composed of four logical layers: data acquisition via the Android Telephony API, data management through an embedded SQLite database, local processing and analysis, and visualization using Flutter’s cross-platform UI with OpenStreetMap for spatial rendering. Field validation demonstrates that the tool reliably collects LTE KPIs such as RSRP, RSRQ and SINR, while producing georeferenced heatmaps and analytical reports comparable in accuracy to established commercial and open-source tools. A comparative evaluation against GNetTrack Pro confirms that the proposed solution offers equivalent or superior functionality, including user authentication, automated KPI analysis, signal prediction and PDF report export, at effectively zero licensing cost. The resulting application constitutes a portable, operator-independent and cost-effective platform suited to network optimization, academic research and educational training linked to mobile radio engineering.

References

• Statista. 2023. Forecast number of mobile users worldwide 2019–2023. Statista, 16 November 2023. https://www.statista.com/statistics/218984/number-of-global-mobile-users-since-2010/
• Amaldi, E., Capone, A., and Malucelli, F. 2007. Radio planning and coverage optimization of 3G cellular networks. Wireless Networks 14, 4 (2007), 435–447. https://doi.org/10.1007/s11276-006-0729-3
• Mishra, A. R. 2004. Fundamentals of Cellular Network Planning and Optimisation. John Wiley & Sons, Ltd. https://doi.org/10.1002/0470862696
• Mousa, A. M. 2012. Prospective of fifth generation mobile communications. International Journal of Next-Generation Networks 4, 3 (2012), 11–30. https://doi.org/10.5121/ijngn.2012.4302
• Richa. 2024. Study and implementation of drive test for development of GSM network. International Journal of Engineering Trends and Technology (IJETT). Seventh Sense Research Group. https://ijettjournal.org/archive/ijett-v4i10p113
• Varol, A. and Çetin, B. K. 2020. A new mobile application for physical measurement in a cellular network. Journal of Scientific Reports-A, 045 (2020), 178–200.
• Samani Siewe, D. 2023. A new mobile RF drive test application. TechRxiv, 28 August 2023. https://doi.org/10.36227/techrxiv.24040917.v1
• Kaup, F., Jomrich, F., and Hausheer, D. 2015. Demonstration of NetworkCoverage – A mobile network performance measurement app. ResearchGate, March 2015. https://www.researchgate.net/publication/270568803_Demonstration_of_NetworkCoverage_-_A_Mobile_Network_Performance_Measurement_App
• Nikravesh, A., Yao, H., Xu, S., Choffnes, D., and Mao, Z. M. 2015. Mobilyzer. https://doi.org/10.1145/2742647.2742670
• Huang, J., Chen, C., Pei, Y., Wang, Z., Qian, Z., Qian, F., …, and Bahl, P. 2011. MobiPerf: Mobile network measurement system. Technical Report. University of Michigan and Microsoft Research.
• Wu, D., Li, W., Rocky, C., and Gao, D. 2016. MopEye: Monitoring per-app network performance with zero measurement traffic. arXiv. https://arxiv.org/abs/1610.01282
• Sonntag, S., Schulte, L., and Manner, J. 2025. Mobile network measurements – It’s not all about signal strength. Aalto University Research Portal. https://research.aalto.fi/en/publications/mobile-network-measurements-its-not-all-about-signal-strength
• Lauridsen, M., Rodriguez, I., Mikkelsen, L. M., Gimenez, L. C., and Mogensen, P. 2016. Verification of 3G and 4G received power measurements in a crowdsourcing Android app. VBN Forskningsportal (Aalborg Universitet). https://doi.org/10.1109/wcnc.2016.7564930
• Deussom Djomadji, E. M., Kabiena Ivan, B., and Chiegue Tchuinmogne, H. Y. 2022. Web based 4G drive tests post processing software for educational and enterprise purpose. European Journal of Applied Sciences 10, 3 (2022), 231–257. https://doi.org/10.14738/aivp.103.12348